R Notebook

library(tidyverse)
library(plotly)
f1 <- read_csv("https://github.com/ruhani13/Dataset/raw/main/race_wins_1950-2020.csv",show_col_types = FALSE)

New names:
* `` -> ...1

constructors<-read_csv("https://github.com/ruhani13/Dataset/raw/main/constructors_championship_1958-2020.csv",show_col_types = FALSE) %>% 
  filter(Year %in% (2011:2020))

top_drivers<-f1 %>% 
  group_by(Name) %>% 
  summarise(n=n()) %>% 
  arrange(desc(n)) %>% 
    top_n(15,n)
best_drivers<-top_drivers %>% 
  ungroup() %>% 
  pull(Name)

top_drivers<-filter(f1,Name %in% best_drivers)
p<-ggplot(top_drivers,aes(x = forcats::fct_rev(fct_infreq(Name)), fill = Team,text=paste("Race Wins: ", ..count..)))+
  geom_bar() +
  coord_flip()+
  xlab("Drivers")+
  ylab("Race Wins")+
  ggtitle("Best Driver since 1950 with most race wins")+
  theme_classic()+
  viridis::scale_fill_viridis(discrete=T,option = "D") 
ggplotly(p,tooltip = c("Team","text")) %>% 
  hide_legend()

constructors_champs<-constructors %>% 
  group_by(Team) %>% 
  summarise(n=sum(Points) )%>% 
  arrange(desc(n)) %>% 
   top_n(10,n)
best_teams<-constructors_champs %>% 
  ungroup() %>% 
  pull(Team) 

constructors_champs<-filter(constructors,Team %in% best_teams)
p<-ggplot(constructors_champs,aes(as.factor(Year),Points,col=Team,text=paste("Position: ",Position)))+
  geom_point(aes(size=Points))+
  xlab("Year")+
  ggtitle("F1 constructor standings")+
 scale_colour_viridis_d(option = "plasma")+
  theme_classic()
ggplotly(p,tooltip = c("Team","y","text")) %>% 
  layout(legend = list(orientation = 'h',y=-0.2))

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